Triple
T30949526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fujifilm X-S20 |
E788495
|
entity |
| Predicate | internalBitDepth |
P176344
|
FINISHED |
| Object | 10-bit |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 10-bit | Statement: [Fujifilm X-S20, internalBitDepth, 10-bit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: internalBitDepth Context triple: [Fujifilm X-S20, internalBitDepth, 10-bit]
-
A.
videoBitDepthInternal
chosen
Indicates the number of bits used internally to represent each color component of video data during processing or storage.
-
B.
supportsBitDepthUpTo
Indicates the maximum bit depth value that an entity can handle, process, or is compatible with.
-
C.
colorDepth
Indicates the bit-depth used to represent the color information of an image or display, defining how many distinct colors can be shown.
-
D.
extraBitplanesUsedFor
Indicates that additional bitplanes are utilized to provide extra data or capabilities for a specified target (such as an image, layer, or graphical element).
-
E.
supportsAlphaBitDepth
Indicates that one entity is capable of handling or providing image or video data with an alpha (transparency) channel at a specified bit depth.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f224c180f88190ad177372ee02b7e2 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd0b92f42881908cd77e3f058adcc2 |
completed | May 7, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fd0a3d68d4819094d92040f7c48d7c |
completed | May 7, 2026, 9:55 p.m. |
Created at: April 29, 2026, 8:53 p.m.